Data Modeling and Design Quiz Set

Which of these statements is NOT true of Data Modelling, according to the DMBOK?

Data modeling is the process of discovering, analyzing, and scoping data requirements
Data modeling involves representing and communicating these data requirements in a precise form called the data model
Data modelling designs how data fits together
Data models depict and enable an organisation to understand its data assets
Data models are only relevant for a technical audience

The highest level of these data model types is the:

Operating Model
Conceptual Model
Logical Model
Physical Model
Super Model

Data Models are critical to Managing Data. Which of the following statements are true?

Data Models enable a common vocabulary around data
Data Models exist to document knowledge about an organisation’s data and systems
Data Models are used as communication tools during projects
Data Models are the starting point when customising, integrating or replacing an application
All of the above

Data Model diagrams:

Use standard symbols that enable the user to understand content
Are not useful for communicating business requirements
Do not belong in the metadata repository
Never model category information
Are only ever created as part of the system development life cycle (SDLC)

Which of these is NOT a building block commonly used in data models?

Entities
Relationships
Categories
Attributes
Domains

Employee, Patient, Competitor and Student are examples of which Entity category?

Where
Where
How
Who
When

Entity type, Entity instance, Dimension, Object, Hub and Node are all examples of what?

Data Models
Entity Alias
Schemas
Values
Measures

Entity definitions are essential to the value of the data model and act as core Metadata for the business. Which three characteristics does the DMBOK say are essential to create high-quality definitions?

Clarity, Accuracy and Completeness
Clarity, Timeliness and Completeness
Creativity, Timeliness and Completeness
Concise, Accurate and Controlled
None of the above

Which of these best describes relationship labels?

The verb phrases describing the business rules in each direction between two entities
An identifying relationship
A foreign key that has been fact-named
A relationship with no cardinality
None of the above

What does relationship cardinality achieve?

Cardinality ensures valid values
Cardinality rules are the same as referential integrity rules
Cardinality rules show how many of each entity that can participate with how many of another entity they are related to
Cardinality rules determine the attributes used by each entity
Cardinality rules are only useful in NoSQL

A relationship label that states “Each student may attend one or many courses” is an example of what type of rule?

Cardinality rule
Referential integrity rule
Student management rule
Connection rule
None of the above

Unary, Binary and Ternary are examples of what?

Quality of relationships
Power of relationships
Clarity of relationships
Arity of relationships
Parity of relationships

In a hierarchical recursive relationship, which of these statements is true?

An entity instance can have more than one parent
An entity instance has no parent entities
An entity instance has no child entities
Many entity instances can have many parents
An entity instance can have more than one child, but only one parent

If a student can register for a course, in a given semester, and we have modelled Student, Course and Semester as entities, what type of relationship does this describe?

Recursive relationship
Ternary relationship
Teaching relationship
Unary relationship
Binary relationship

In data modelling, what is a foreign key?

A key that is not recognised by the system
A representation of a relationship between two entities
A key to understanding conceptual data models
A quality key
None of the above

Which of these will you NOT find in a data model?

Primary key
Surrogate key
Foreign key
Alternate key
Local key

In Data Modelling, which of these is TRUE for an attribute?

Attributes may have domains
Attributes may identify an entity
Attributes may describe an entity
Attributes may measure an entity
All of the above

Identifiers, or keys, are used to help uniquely identify instances of an entity. Which of the following are examples of Construction type keys?

Candidate, Primary, Alternate
Column, Field, Tag
Candidate, Primary, Nonfunctional
Simple, Compound, Composite
Simple, Compound, Alternate

Which of these is TRUE about surrogate keys?

Surrogate keys are a set of two or more attributes that together uniquely identify an entity instance
Surrogate keys are an example of a simple key
Surrogate keys contain one compound key and at least one other simple or compound key or non-key attribute
Surrogate keys have a meaning that is related to its face value
None of the above

Which of these would make for a good Candidate Key for a customer entity?

A counter that is system generated without intelligence
A key that is not visible to end users of a database
An Alternate Key
The customers weight in pounds
A customers mobile phone number

In a non-identifying relationship:

The primary key of the child entity is concatenated
The primary key of the parent entity becomes part of the primary key of the child entity
The primary key of the child entity is removed
The primary key of the parent entity becomes a foreign key in the child entity
The foreign key of the parent entity migrates to the child entity

In data modelling, what does a domain refer to?

The complete set of possible values that an attribute can be assigned
The highest level of entity in a conceptual data model
The six most common schemes used to represent data
A non-identifying relationship
None of the above

A drop down list showing different order statuses (e.g. Open, Closed, Shipped) is an example of what?

A Primary key
Good database design choices
Master data management
A type of data domain
A data type that is permitted

Which of the following data modelling schemes would be most appropriate for analyzing and reporting on large amounts of transactional data in a data warehouse environment?

Dimensional
Object-Oriented
NoSql
Fact-Based
None of the above

What are the major design objectives for the relational data modelling scheme?

Optimising the query of large volumes of information
Removing attributes, thereby reducing the need for expert judgment
Having an exact representation of business data and keeping one fact in one place
Capturing business questions focused on a particular business process
Enabling the data values to be associated in chronological order

When would dimensional data modelling be more appropriate than relational data modelling?

When you have large amounts of data to query and analyse
When aiming to reduce or remove the redundancy in data storage
When you need to enable quick data capture
When you need accurate data storage
When you need to store the business subject in a document

What are fact tables used for?

Storing mostly textual descriptions of facts
Storing numeric measurements, such as counts and quantities
Storing documents and other unstructured data
Storing the important objects of the business
Storing metadata

Dimension tables:

Store mostly textual descriptions of facts
Store the important objects of the business
Serve as the primary source for ‘query by’ or ‘report by’ constraints
Act as the entry points or links into the fact tables
All of the above

In dimensional data modelling, grain refers to:

The description of the row in a fact table, showing the most detail that row can have
The ability to normalise the flat, single-table, dimensional structure in a star schema into the respective component hierarchical or network structures
The unique identifier chosen for each row
The most important objects of the business
None of the above

Data Vaults:

Are designed specifically to meet the needs of enterprise data warehouses
Are detail-oriented, time-based, and uniquely linked set of normalized tables that support one or more functional areas of business
Are a hybrid between 3NF and star schema
Include three types of entities, hubs, links and satellites
All of the above

Which of these is NOT a type of NoSQL database?

Document
Key-value
Column-oriented
Graph
Node

Which of these is a good reason to denormalise data?

Improving performance when running queries
Reducing costly run time calculations
Enforcing user security by segregating views according to user needs
All of the above
None of the above

Which of these is the correct description of the third normal form (3NF)?

Ensures each entity has no hidden primary keys and that each attribute depends on no attributes outside the key (“the key, the whole key and nothing but the key”)
Ensures each entity has the minimal primary key and that every attribute depends on the complete primary key
Ensures each entity has a valid primary key, and every attribute depends on the primary key
Resolves all many-to-many-to-many relationships (and beyond) in pairs until they cannot be broken down into any smaller pieces
Resolves inter-entity dependencies into basic pairs, and all join dependencies use parts of primary keys

Which of these is NOT a deliverable of the data modelling process?

Data Lineage
Definitions for entities, attributes and relationships
A data model diagram
A risk matrix
A list of unresolved business questions

Which of these is NOT a step in the creation of a Conceptual Data Model?

Select Scheme
Select Notation
Collect the highest level nouns for the organisation
Collect the verbs (activities) that connect the organisational nouns
Figuring out how the initial CDM fits with other departments or the organisation as a whole

When designing a logical data model by analysing existing documentation, which of these should you do?

Ensure the data model is not out of date, as you cannot reuse old data models
Only rely on data models from systems that are in production
Validate any new work with business SMEs to ensure accuracy and consistency
Ignore any data models that come from packaged applications
Never design a data model based on existing documentation, it's always best to take a top-down approach and start fresh

Which of these is NOT a step used in the creation of a Logical Data Model?

Add Associative Entities
Add Attributes
Assign Domains
Assign Keys
Performing physical database design, such as determining file organization, block sizes, or disk allocation.

Which of these is NOT TRUE of physical data modelling?

Logical data models need adaptations to ensure they perform well in storage applications
The physical domain, physical data type, and length of each column or field must be defined
Unique key values must be assigned that are not visible to the business and have no meaning or relationship with the data with which they are matched
Using as many columns and tables as possible to store information, so that the database is more efficient.
Logical abstraction entities (supertypes and subtypes) become separate objects in the physical database design using one of two methods

Which of these is NOT a useful tool when creating a data model?

Metadata repository
Data Profiling Tools
Data Lineage Tools
Data Modelling Tools
Data Mining Tools

Industry data models:

Are data models pre-built for an entire industry
Are often both broad in scope and very detailed
Can be purchased through vendors or obtained through industry groups
Need to be customized to fit an organisation
All of the above

How does ISO 11179 connect Data Modelling to other data management disciplines?

These standards ensure the models conforms with Enterprise Architecture and Data Architecture and ensures the quality of data
Naming standards should reflect their specific environment, such as test, QA, or production
The standards ensure performance and ease of use, reusability, integrity and security
ISO 11179 does not connect data modelling and other data management areas
All of the above

What is the role of data analysts and designers in the Data Governance process?

They ensure the fastest possible response to changes in business processes and new business requirements
They ignore the privacy concerns of all stakeholders, including customers, business partners, and government regulators
They act as intermediaries between data producers and data consumers and balance the needs of both stakeholder groups
There is no role for data analysts and designers in data governance
They act as the Business Data Steward

Which of these is NOT a suitable agenda item for reviewing data model and database design quality?

Reviewing the starting model (if any)
Reviewing the changes made to the model
Discussing the options that were considered but rejected when changing the model
Determining the data quality dimensions to be used by the model
Analysing the fit between the model and the existing standards in place

Which of these is NOT a metric used to determine the quality of a data model?

The visualisation quality of the model for business users
How well the model follows naming standards
The quality of the definitions
The completeness of the model
The fit between the metadata and the data itself

Which of these groups has primary responsibility for data capture and usage design within programs?

The Chief Data Officer
Software Architects, Developers
Suppliers, Consumers
Business users of the application
Business Data Stewards, Subject Matter Experts (SMEs)

Data Modeling and Design Quiz Set

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